P2-LOAM: LiDAR Odometry and Mapping with Pole-Plane Landmark

For spatial perception, object-level SLAM (Simultaneous Localization and Mapping) has shown an advantage by leveraging semantic information to comprehend unknown environments. Poles are considered significant semantic landmark objects in urban roads and man-made constructions like stone pillars, str...

Full description

Saved in:
Bibliographic Details
Published in:IEEE Conference on Industrial Electronics and Applications (Online) pp. 1 - 7
Main Authors: Xu, Jianhong, Chen, Weinan, Mao, Shixin, Guan, Yisheng, Zhu, Haifei
Format: Conference Proceeding
Language:English
Published: IEEE 05.08.2024
Subjects:
Accuracy
Design methodology
Industrial electronics
Laser radar
Location awareness
pole landmark
Roads
Simultaneous localization and mapping
SLAM
ISSN:2158-2297
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:For spatial perception, object-level SLAM (Simultaneous Localization and Mapping) has shown an advantage by leveraging semantic information to comprehend unknown environments. Poles are considered significant semantic landmark objects in urban roads and man-made constructions like stone pillars, street light lamps, and tree trunks. The rich pole land-marks enhance to the robustness and accuracy of SLAM. In this paper, we propose a LiDAR-based object-level SLAM named p 2 - LOAM, which simultaneously estimates the pose and constructs a sparse pole landmark map. We propose a multi-RANSAC method for pole segmentation and estimate the parametric representation of pole objects in various scenes. Based on the segmented pole outcome, a coarse-to-fine data association for the pole object method is designed. Furthermore, a plane-assisted cost function for the pole landmark residual construction is developed. We demonstrate the accuracy and robustness of the proposed method in public datasets and real-world experiments.
ISSN:2158-2297
DOI:10.1109/ICIEA61579.2024.10665090